Feature Engineering
If you like applying Feature Engineering, every challenge here gives you a chance to practice it on a real industry brief.
- CodeAdvancedNew
Build a Streaming Pipeline for Real-Time Fraud Detection
Receive 30 days of anonymized card-transaction events (around 240M events total), the team's existing batch features (cardholder behavior summaries), and a pre-trained fraud-sco…
- Stream Processing
- Kafka
- Flink
Big Data and Data-Intensive Systems - CodeAdvancedNew
Detect Coordinated Fraud Rings via Link Analysis at a Neobank
You receive 90 days of account, login, and transaction data (around 1.2 million accounts, around 30 million events) plus a labeled set of 80 known fraud rings. Build a multi-rel…
- Graph Analysis
- Community Detection
- Link Analysis
Data Mining and Knowledge Discovery - CodeAdvancedNew
Predict Loan Default Risk for a Cross-Border Fintech
You receive 18 months of transactions (around 12M rows) and seller-firmographic data. Define a defensible proxy label for default (e.g., a 60-day chargeback-or-dispute spike com…
- Feature Engineering
- Model Selection
- Model Evaluation
Applied Machine Learning - CodeAdvancedNew
Build an Anomaly-Detection Pipeline for Pharma Cold-Chain Logistics
You receive 18 months of shipment telemetry (around 60,000 shipments, around 12 million sensor readings) plus a hand-labeled set of 1,200 incidents (mix of true excursions, sens…
- Anomaly Detection
- Feature Engineering
- Time Series
Data Mining and Knowledge Discovery Practice your coursework on real scenarios.
Every challenge is shaped from real industry context — not generic exercises. The work mirrors what your degree prepares you for.
Why Ewance
- AnalysisAdvancedNew
Structured Prediction for Insurance Claim Triage
You receive 18,000 historical claims with text, attachments-count, claim amount, customer tenure, and the ground-truth final routing bucket. Train a structured classifier (e.g.,…
- Structured Prediction
- Multi Class Classification
- Model Evaluation
Advanced Machine Learning - CodeAdvancedNew
Forecast Energy Demand for a Nordic Renewable Utility
You receive 5 years of hourly residential-segment demand, hourly weather data (temperature, wind, irradiance), and a calendar of public holidays. Build a probabilistic forecaste…
- Time Series Forecasting
- Probabilistic Modeling
- Feature Engineering
Applied Machine Learning - AnalysisAdvancedNew
Forecasting Churn for a SaaS Scale-Up
You are a data scientist intern at TaskFlow. Using the provided dataset, perform feature engineering and build a logistic regression or decision tree model to predict churn. Ide…
- Data Analysis
- Regression
- Classification
Data Analytics for Business - CodeAdvancedNew
Build an End-to-End ML Pipeline for Loan-Default Prediction
You receive 24 months of historical application + outcome data (about 380,000 rows). Build a pipeline using a workflow orchestrator (Prefect, Kedro, or a simple Makefile chain) …
- Ml Pipelines
- Feature Engineering
- Pipeline Testing
Machine Learning in Practice - Browse challenges
Explore role
Product Manager
Ship product that solves real user problems. Combine user research, prototyping, and stakeholder alignment to turn ambiguous briefs into measurable wins — the role at the centre of modern software teams.
- CodeAdvancedNew
Build a Real-Time Fraud-Detection Stream for a Card Issuer
Design the stream topology: authorization events in, customer-feature state (30-day rolling) maintained in state store, scoring function applied per event, fraud-score emitted t…
- Apache Flink
- Kafka Streams
- Stream Processing
Event-Driven Architecture - AnalysisAdvancedNew
Capstone Lab: Diagnose Why a Production Model Quietly Stopped Working
You receive 6 months of production logs (model inputs, predictions, ground truth from chargebacks) plus the original training data and model card. Reproduce the recall drop in a…
- Data Drift Detection
- Model Monitoring
- Root Cause Analysis
AI/ML Practicum and Hands-on Lab - DesignAdvancedNew
Stand Up a Feature Store for a Series-B Fintech
Pick one priority feature group (recommend the 25 transaction-history features used by the fraud model). Define the offline source-of-truth (likely Snowflake or BigQuery), the o…
- Feature Store
- Feature Engineering
- Airflow
ML Engineering and Production ML - CodeAdvancedNew
Forecast Intraday FX Volatility for a London Liquidity Desk
You receive 18 months of tick-level mid-quote data for six FX pairs plus a calendar of scheduled macro events. Resample to 1-minute bars, engineer realized-volatility features, …
- Time Series Forecasting
- Feature Engineering
- Model Validation
AI and Quantitative Finance Build a verifiable portfolio.
Submissions become evidence. Reviewers with shipping experience score against a rubric; the result becomes a credential anyone can verify.
Why Ewance
- CodeAdvancedNew
Build a Feature Store Backbone for a Healthtech ML Team
You receive synthetic wearable telemetry (heart rate, accelerometer, sleep stages) for around 5,000 patients across 90 days, plus the existing scattered feature scripts from the…
- Feature Engineering
- Data Modeling
- Python
Data Engineering and Big Data Systems
How it works
From brief to credential, in six steps.
Step 01
Browse challenges aligned to your studies.
Step 02
Accept the one that fits your goals.
Step 03
Work through it with AI Copilot guidance.
Step 04
Submit for structured evaluation.
Step 05
Earn a verified credential.
Step 06
Add it to LinkedIn with one click.
Industry teams behind a decade of practitioner briefs
Hiring from this pool?
Sponsor a challenge and meet candidates through actual work.
Industry teams can shape briefs around the skills they hire for, then evaluate students on rubric-scored deliverables — not resumes.